TASC 2.4 Streamlit GUI

Show Example Input

# Example input for a typical analysis run:
path = "D:\jeries\output\TASC_pickles\"
ST = "rawdata.pickle"
STgraph = "rawdatagraph.pickle"
MorphoFeatures = ['Area', 'Ellip_Ax_B_X', 'Ellip_Ax_B_Y']
BpwFeatures = ['Velocity_Full_Width_Half_Maximum', 'Velocity_Maximum_Height']
SAMPLE = False
expList = [16,17,18,19,20,21,22,23]
CellSample = 2
expListT = [0,1,2,3,4,5,6,7,8,9,10,11]
title = "jeries_test"
k_cluster = 3
MorphoOut = False
MorphoIn = False
combin = [["NNIR"],["METR"],["GABY"]]
singleTREAT = False
singleCONTROL = True
multipleCL = False
nrows = 1
ncols = 12
nColor = 12
nShades = 2
nColorTreat = 0
nShadesTreat = 0
nColorLay = 3
nShadesLay = 3
figsizeEXP = (25,5)
figsizeTREATS = (15,5)
figsizeCL = (15,15)
CON = ['NNIR']
CL = ['293T']
wellCON = ['AM001100425CHR2B02293TNNIRNOCOWH00']
controls = []

Drag and drop file hereLimit 200MB per file • XLSX

summary_table.xlsx
49.9MB

AreaEllip_Ax_B_XEllip_Ax_B_YEllip_Ax_C_XEllip_Ax_C_YEllipsoidAxisLengthBEllipsoidAxisLengthCEllipticity_oblateEllipticity_prolateSphericityEccentricity

Velocity_Full_Width_Half_MaximumVelocity_Time_of_Maximum_HeightVelocity_Maximum_HeightVelocity_Ending_ValueVelocity_Ending_TimeVelocity_Starting_ValueVelocity_Starting_Time

Sampling
If you want to sample cells to balance well sizes, check this box.

expList: Indices of wells to sample (comma-separated).
CellSample: Sampling divisor (e.g., 2 for half, 3 for a third).

Experiments to analyze (without sampling)
Indices for the wells you wish to analyze without sampling.
You can use a comma-separated list (e.g., 0,1,2,3,4,5,6,7,8,9,10,11) or a Python range (e.g., range(0,12)).

Experiment title and number of clusters
Choose a unique title for this run. All output files will use this as a prefix.
Set the number of clusters for k-means analysis.

Feature selection
Check to analyze only kinetics (BPW) or only morphology.
If you wish to run on the entire feature list, leave both unchecked.

Treatments Combination

Specify how your treatments can be combined in your experiments.

Each treatment name should be 4 characters long.
Treatments that are not combined with each other should be placed in the same list.
Treatments that can be combined with others should be in separate lists.

Example:
If your treatments are HGF2, HGF7, DOX1, PHA4, PHA3:

If HGF2, HGF7, and DOX1 are not combined with each other, put them in the same list: ['HGF2', 'HGF7', 'DOX1']
If PHA4 and PHA3 are not combined with the others, put them in another list: ['PHA4', 'PHA3']
The format is: [['HGF2', 'HGF7', 'DOX1'], ['PHA4', 'PHA3']]

You will not find a well named 'HGF2HGF7' or 'HGF2DOX1', but you may find 'HGF7PHA4'.

Note:
If you have a control well (e.g., 'CON'), do not include it in any list.

Single/multiple treatment/control/cell lines

singleTREAT: True if only one treatment.
singleCONTROL: True if only one control.
multipleCL: True if multiple cell lines.

Graph Properties

These settings control the appearance and layout of your output figures. You may need to adjust them depending on your experiment and preferences.

nrows, ncols:
Set the number of rows and columns in your experiment figures. For example, if you have 3 cell lines and 8 treatments, use nrows=3 and ncols=8.
Default: nrows=0, ncols=1
nColor, nShades:
Define the number of colors and shades used in the experiment figures.
Default: nColor=0, nShades=0
nColorTreat, nShadesTreat:
Number of colors and shades for treatment-specific figures. Usually, you can leave these at their default values.
Default: nColorTreat=0, nShadesTreat=0
nColorLay, nShadesLay:
Number of colors and shades for y-position (layer) figures.
Example: nColorLay=3, nShadesLay=3
figsizeEXP, figsizeTREATS, figsizeCL:
Set the figure size for experiment, treatment, and cell line figures as (width, height) tuples.
Example:
- figsizeEXP = (40, 15)
- figsizeTREATS = (30, 15)
- figsizeCL = (15, 5)

Tip: You may need to revisit and adjust these settings to get the best visualization for your data.

Chi-Squared Test Variables

CON:
List of control names (comma-separated).
Example: CON = ['CON'] or CON = ['CON1', 'CON2']
CL:
List of cell lines (comma-separated).
Example: CL = ['BT54', 'MDA2', 'MCF7'] or CL = ['293T']

wellCON:
List of well names for controls (one per line, without the 'NNN0' part).
Example:

HA033080917CHR1C02BT54CON0WH00
HA033080917CHR1D02MDA2CON0WH00
HA033080917CHR1F02MCF7CON0WH00

controls:
List of specific experiment names to use as controls (one per line).
Example:
```
BT54HGF7
```
Leave blank if not used.

Analysis is running...

Experiment Names in Order (Unique)

These are the unique experiment names found in your data:

value
AM001100425CHR2B02293TNNIRNOCONNN0NNN0NNN0WH00
AM001100425CHR2B03293TNNIRNOCONNN0NNN0NNN0WH00
AM001100425CHR2B04293TNNIRNOCONNN0NNN0NNN0WH00
AM001100425CHR2C02293TMETRNNIRNOCONNN0NNN0WH00
AM001100425CHR2C03293TMETRNNIRNOCONNN0NNN0WH00
AM001100425CHR2C04293TMETRNNIRNOCONNN0NNN0WH00
AM001100425CHR2D02293TGABYNNIRNOCONNN0NNN0WH00
AM001100425CHR2D03293TGABYNNIRNOCONNN0NNN0WH00
AM001100425CHR2D04293TGABYNNIRNOCONNN0NNN0WH00
AM001100425CHR2E02293TNNIRMETRGABYNOCONNN0WH00
AM001100425CHR2E03293TNNIRMETRGABYNOCONNN0WH00
AM001100425CHR2E04293TNNIRMETRGABYNOCONNN0WH00

Number of Cells per Experiment

Index #	Experiment	Number of Cells
0	AM001100425CHR2B02293TNNIRNOCONNN0NNN0NNN0WH00	9228
1	AM001100425CHR2B03293TNNIRNOCONNN0NNN0NNN0WH00	16861
2	AM001100425CHR2B04293TNNIRNOCONNN0NNN0NNN0WH00	23874
3	AM001100425CHR2C02293TMETRNNIRNOCONNN0NNN0WH00	5791
4	AM001100425CHR2C03293TMETRNNIRNOCONNN0NNN0WH00	5362
5	AM001100425CHR2C04293TMETRNNIRNOCONNN0NNN0WH00	5362
6	AM001100425CHR2D02293TGABYNNIRNOCONNN0NNN0WH00	5672
7	AM001100425CHR2D03293TGABYNNIRNOCONNN0NNN0WH00	8852
8	AM001100425CHR2D04293TGABYNNIRNOCONNN0NNN0WH00	5446
9	AM001100425CHR2E02293TNNIRMETRGABYNOCONNN0WH00	8205
10	AM001100425CHR2E03293TNNIRMETRGABYNOCONNN0WH00	8950
11	AM001100425CHR2E04293TNNIRMETRGABYNOCONNN0WH00	6184

Sampling Cells

If sampling is enabled, only a subset of cells from selected wells will be used. For example, CellSample=2 means every second cell track is sampled.

Sampling is disabled. All cells from selected wells will be used.

Experiments to Analyze

The following experiments will be analyzed (excluding sampled experiments if sampling is enabled):

expListT:

[
0:
0
1:
1
2:
2
3:
3
4:
4
5:
5
6:
6
7:
7
8:
8
9:
9
10:
10
11:
11
]

The experiment(s) you chose:

AM001100425CHR2B02293TNNIRNOCOWH00

AM001100425CHR2B03293TNNIRNOCOWH00

AM001100425CHR2B04293TNNIRNOCOWH00

AM001100425CHR2C02293TMETRNNIRNOCOWH00

AM001100425CHR2C03293TMETRNNIRNOCOWH00

AM001100425CHR2C04293TMETRNNIRNOCOWH00

AM001100425CHR2D02293TGABYNNIRNOCOWH00

AM001100425CHR2D03293TGABYNNIRNOCOWH00

AM001100425CHR2D04293TGABYNNIRNOCOWH00

AM001100425CHR2E02293TNNIRMETRGABYNOCOWH00

AM001100425CHR2E03293TNNIRMETRGABYNOCOWH00

AM001100425CHR2E04293TNNIRMETRGABYNOCOWH00

The cell line(s):

293T

The treatments are:

Number of features: 49

The Features are:

Area

Acceleration

Acceleration_OLD

Acceleration_X

Acceleration_Y

Coll

Coll_CUBE

Confinement_Ratio

Directional_Change

Overall_Displacement

Displacement_From_Last_Id

Displacement2

Ellip_Ax_B_X

Ellip_Ax_B_Y

Ellip_Ax_C_X

Ellip_Ax_C_Y

EllipsoidAxisLengthB

EllipsoidAxisLengthC

Ellipticity_oblate

Ellipticity_prolate

Instantaneous_Angle

Instantaneous_Speed

Instantaneous_Speed_OLD

Linearity_of_Forward_Progression

Mean_Curvilinear_Speed

Mean_Straight_Line_Speed

Current_MSD_1

Final_MSD_1

MSD_Linearity_R2_Score

MSD_Brownian_Motion_BIC_Score

MSD_Brownian_D

MSD_Directed_Motion_BIC_Score

MSD_Directed_D

MSD_Directed_v2

Sphericity

Total_Track_Displacement

Track_Displacement_X

Track_Displacement_Y

Velocity_X

Velocity_Y

Eccentricity

Min_Distance

Velocity_Full_Width_Half_Maximum

Velocity_Time_of_Maximum_Height

Velocity_Maximum_Height

Velocity_Ending_Value

Velocity_Ending_Time

Velocity_Starting_Value

Velocity_Starting_Time

Features Used for Analysis

0
Area
Acceleration
Acceleration_OLD
Acceleration_X
Acceleration_Y
Coll
Coll_CUBE
Confinement_Ratio
Directional_Change
Overall_Displacement
Displacement_From_Last_Id
Displacement2

Histogram of Features

\color{blue}{\Large Figure\ 1}

KDE Histogram of Features

\color{blue}{\Large Figure\ 2}

\color{blue}{\Large Figure\ 3}

\color{blue}{\Large Figure\ 4}

There are 1 significant components

\color{blue}{\Large Figure\ 5}

\color{blue}{\Large Figure\ 6}

\color{blue}{\Large Figure\ 7}

\color{blue}{\Large Figure\ 8}

\color{blue}{\Large Figure\ 9}

\color{blue}{\Large Figure\ 10}

\color{blue}{\Large Figure\ 11}

\color{blue}{\Large Figure\ 12}

\color{blue}{\Large Figure\ 13}

\color{blue}{\Large Figure\ 14}

\color{blue}{\Large Figure\ 15}

$0$

\color{blue}{\Large Figure\ 16}

\color{blue}{\Large Figure\ 17}

\color{blue}{\Large Figure\ 18}

\color{blue}{\Large Figure\ 19}

\color{blue}{\Large Figure\ 20}

\color{blue}{\Large Distribution\ all\ features\ by\ groups}

\color{blue}{\Large Figure\ 21}

\color{blue}{\Large Figure\ 22}

\color{blue}{\Large Figure\ 23}

\color{blue}{\Large Figure\ 24}

\color{blue}{\Large Figure\ 25}

\color{blue}{\Large Figure\ 26}

Treatments p-Value

	0	1	2	All	N	Pearson Chi-square ( 2.0) =	p-value =	Cramer's V =
NNIRGABY	49.01	29.04	21.95	100	19970	5695.1707	0	0.2854
NNIRMETR	45.73	53.05	1.21	100	16515	2291.3618	0	0.1857
NNIRMETRGABY	39.47	39.82	20.71	100	23339	3023.1567	0	0.2031
NNIR	29.73	60.19	10.08	100	49963
All					109787

\color{blue}{\Large Figure\ 27}

\color{blue}{\Large Figure\ 28}

Experiments p-Value AM001100425CHR2B02293TNNIRNOCOWH00

	0	1	2	All	N	Pearson Chi-square ( 2.0) =	p-value =	Cramer's V =
AM001100425CHR2B03293TNNIRNOCOWH00	30.34	60.17	9.49	100	16861	1052.3214	0	0.2008
AM001100425CHR2B04293TNNIRNOCOWH00	26.59	67.24	6.17	100	23874	2408.0533	0	0.2697
AM001100425CHR2C02293TMETRNNIRNOCOWH00	38.63	60.65	0.73	100	5791	1383.2243	0	0.3035
AM001100425CHR2C03293TMETRNNIRNOCOWH00	49.57	48.96	1.47	100	5362	1123.6414	0	0.2775
AM001100425CHR2C04293TMETRNNIRNOCOWH00	49.57	48.96	1.47	100	5362	1123.6414	0	0.2775
AM001100425CHR2D02293TGABYNNIRNOCOWH00	53.49	29.83	16.68	100	5672	405.5762	0	0.165
AM001100425CHR2D03293TGABYNNIRNOCOWH00	48.59	28.08	23.33	100	8852	404.8335	0	0.1496
AM001100425CHR2D04293TGABYNNIRNOCOWH00	45.04	29.76	25.19	100	5446	218.1478	0	0.1219
AM001100425CHR2E02293TNNIRMETRGABYNOCOWH00	37.95	32.77	29.27	100	8205	209.2255	0	0.1096
AM001100425CHR2E03293TNNIRMETRGABYNOCOWH00	39.73	45.37	14.89	100	8950	125.7056	0	0.0832
AM001100425CHR2E04293TNNIRMETRGABYNOCOWH00	41.11	41.12	17.77	100	6184	42.2356	0	0.0523
AM001100425CHR2B02293TNNIRNOCOWH00	36.74	41.96	21.3	100	9228

\color{blue}{\Large Figure\ 29}

\color{blue}{\Large Figure\ 30}

TimeLayers p-Value 0

	0	1	2	All	N	Pearson Chi-square ( 2.0) =	p-value =	Cramer's V =
1	35.2	51.39	13.42	100	36877	1150.9475	0	0.1238
2	30.52	56.87	12.61	100	34731	2326.2219	0	0.1786
0	46.7	39.87	13.43	100	38179
All					109787

\color{blue}{\Large Figure\ NNIR}

\color{blue}{\Large Figure\ 31}

\color{blue}{\Large Figure\ NNIRGABY}

\color{blue}{\Large Figure\ 32}

\color{blue}{\Large Figure\ NNIRMETR}

\color{blue}{\Large Figure\ 33}

\color{blue}{\Large Figure\ NNIRMETRGABY}

\color{blue}{\Large Figure\ 34}

\color{blue}{\Large Figure\ 35}

\color{blue}{\Large Figure\ 36}

$\color{blue}{\Large Figure\ 37}$

$\color{blue}{\Large Descriptive\ Table}$

Groups	N	Mean	std. Deviation	std. Error	95 confidence Interval for Mean Upper Bound	95 confidence Interval for Mean Lower Bound	N	Mean	std. Deviation	std. Error	95 confidence Interval for Mean Upper Bound	95 confidence Interval for Mean Lower Bound	N	Mean	std. Deviation	std. Error	95 confidence Interval for Mean Upper Bound	95 confidence Interval for Mean Lower Bound
0	41407	1814.536600496393	622.7145837043928	3.060216508564292	1820.5345524250802	1808.5386485677059	41407	-0.471370035193065	8.127756882787914	0.0399423691707079	-0.3930839369600411	-0.5496561334260889	41407	11.394688772437792	7.735494903479775	0.038014669681770474	11.469196625296595	11.320180919578993
1	53925	799.5565271035708	244.1465984336387	1.0513700492977458	801.617193293149	797.4958609139927	53925	-0.4820104515757741	7.127340916670438	0.030692513510313827	-0.42185368288513136	-0.5421672202664168	53925	9.4566378535145	6.961753713486911	0.029979444284319992	9.51539701948114	9.39787868754786
2	14455	1165.293699710916	589.9141878340292	4.906590271024501	1174.9102839861828	1155.677115435649	14455	-0.14005362927129825	15.71015412341302	0.130668648030417	0.11604806182370689	-0.3961553203663034	14455	17.64728390900387	12.321830162702742	0.10248638402733806	17.848150273347855	17.446417544659887

$\color{blue}{\Large Figure\ 38}$

$\color{blue}{\Large ANOVA\ -\ OneWay}$

Could not convert column: Experiment

Could not convert column: Treatments

\color{blue}{\Large ANOVA\ Table\ feature\ per\ Group}

	Sum of Squares	df	Mean Square	F	Sig.	Sum of Squares	df	Mean Square	Sum of Squares	df
Area	24199871121.4377	2	12099935560.71885	54664.91681969461	0	24300399650.83	109784	221347.3698428733	48500270772.2677	109786
Acceleration	1430.9840052894494	2	715.4920026447247	8.6872292714829	0.0001688428897527276	9041959.35937813	109784	82.36135829791344	9043390.343383418	109786
Acceleration_OLD	765843.8705147353	2	382921.9352573677	5770.074055606543	0	7285643.361794911	109784	66.36343512529068	8051487.232309647	109786
Acceleration_X	33.81293991219613	2	16.906469956098064	0.1730969975776198	0.8410562600375047	10722657.95267754	109784	97.67049800223658	10722691.765617453	109786
Acceleration_Y	458.38723668617155	2	229.19361834308577	2.2341344713524394	0.10708964330857419	11262434.074053552	109784	102.58720828220461	11262892.461290238	109786
Coll	22.496987134898646	2	11.248493567449323	158.21764962226948	2.4310018736154865e-69	7805.100257506549	109784	0.07109506173492083	7827.597244641447	109786
Coll_CUBE	20.463977045572477	2	10.231988522786239	162.38064114067302	3.829000367968849e-71	6917.749678130804	109784	0.06301236681238435	6938.213655176376	109786
Confinement_Ratio	494.8935449780636	2	247.4467724890318	6983.507331294593	0	3889.978943560431	109784	0.035433022512938415	4384.8724885384945	109786
Directional_Change	39.590383220109594	2	19.795191610054797	3.2583870558092	0.0384540848473228	666954.3177333046	109784	6.075150456654017	666993.9081165247	109786
Overall_Displacement	374718891.14715314	2	187359445.57357657	38268.73896487885	0	537490127.1695104	109784	4895.887626334533	912209018.3166635	109786
Displacement_From_Last_Id	1197230.934464752	2	598615.467232376	10503.33288111623	0	6256909.230477994	109784	56.99290634771911	7454140.164942746	109786
Displacement2	50583943132793.8	2	25291971566396.9	11827.593642154741	0	234760669875319.5	109784	2138386922.2775586	285344613008113.3	109786

ANOVA & Tukey HSD Results

ANOVA Results

	sum_sq	df	F	PR(>F)
C(Experiment)	31615.424822632183	11	103.74149311533589	8.216526564585167e-224
Residual	253941.50859725944	9166

Tukey HSD Post-hoc Test

	group1	group2	meandiff	p-adj	lower	upper	reject
0	B02293TNNIRNOCO	B03293TNNIRNOCO	-2.4757	0	-3.2945	-1.6569	true
1	B02293TNNIRNOCO	B04293TNNIRNOCO	-3.6504	0	-4.4398	-2.861	true
2	B02293TNNIRNOCO	C02293TMETRNNIRNOCO	-4.6248	0	-5.6777	-3.572	true
3	B02293TNNIRNOCO	C03293TMETRNNIRNOCO	-3.1484	0	-4.1879	-2.109	true
4	B02293TNNIRNOCO	C04293TMETRNNIRNOCO	-3.1484	0	-4.1879	-2.109	true
5	B02293TNNIRNOCO	D02293TGABYNNIRNOCO	0.0272	1	-0.9231	0.9774	false
6	B02293TNNIRNOCO	D03293TGABYNNIRNOCO	1.5664	0	0.7133	2.4196	true
7	B02293TNNIRNOCO	D04293TGABYNNIRNOCO	0.3136	0.9933	-0.5917	1.219	false
8	B02293TNNIRNOCO	E02293TNNIRMETRGABYNOCO	0.2794	0.9968	-0.5989	1.1577	false
9	B02293TNNIRNOCO	E03293TNNIRMETRGABYNOCO	-1.9257	0	-2.8153	-1.0361	true
10	B02293TNNIRNOCO	E04293TNNIRMETRGABYNOCO	-0.8183	0.1488	-1.7477	0.1111	false
11	B03293TNNIRNOCO	B04293TNNIRNOCO	-1.1747	0	-1.8552	-0.4942	true

Analysis complete! You can rerun the analysis by clicking 'Run Analysis' again.